(29 days)
Not Found
Yes
The "Intended Use / Indications for Use" section explicitly mentions "semiautomated machine learning algorithms," and the "Device Description" section states that the device "uses machine learning techniques to aid in semi-automatic contouring." The "Summary of Performance Studies" also details the validation of "Machine Learning Derived Outputs."
No
The device is described as a software application intended for viewing, post-processing, and evaluating cardiovascular MR and CT images for diagnostic information, not for direct treatment or therapy.
Yes
The "Intended Use / Indications for Use" section explicitly states that the device is intended for "Supporting clinical diagnostics" and "for the purpose of obtaining diagnostic information as part of a comprehensive diagnostic decision-making process." It also describes various functionalities like qualitative and quantitative evaluation, measurements, and analysis of medical images to aid in diagnosis.
Yes
The device is explicitly described as "software as a medical device (SaMD)" and its functionality is independent of the acquisition equipment, focusing solely on the processing, visualization, and analysis of pre-acquired images.
Based on the provided information, this device is not an In Vitro Diagnostic (IVD).
Here's why:
- Intended Use: The intended use clearly states that the device is for "viewing, post-processing, qualitative and quantitative evaluation of cardiovascular magnetic resonance (MR) images and computed tomography (CT) images". It supports clinical diagnostics by analyzing images of the heart and blood vessels.
- Nature of the Input: The input is described as "cardiac MR & CT Images in DICOM format". These are medical images, not biological specimens or samples taken from the human body.
- Functionality: The device performs image processing, visualization, and quantitative measurements based on these images. It does not perform tests on biological samples to detect diseases or conditions.
IVDs are typically used to examine specimens (like blood, urine, tissue) in vitro (outside the body) to provide information for diagnosis, monitoring, or screening. This device operates on medical images acquired in vivo (within the body).
No
The letter does not state that the FDA has reviewed and approved or cleared a Predetermined Change Control Plan (PCCP) for this specific device. The 'Control Plan Authorized (PCCP) and relevant text' section explicitly states 'Not Found'.
Intended Use / Indications for Use
cvi42 is intended to be used for viewing, post-processing, qualitative and quantitative evaluation of cardiovascular magnetic resonance (MR) images and computed tomography (CT) images in a Digital Imaging and Communications in Medicine (DICOM) Standard format.
It enables:
- Importing cardiac MR & CT Images in DICOM format.
- Supporting clinical diagnostics by qualitative analysis of cardiac MR & CT images using display functionality such as panning, windowing, zooming, navigation through series/slices and phases, 3D reconstruction of images including multiplanar reconstructions of the images.
- Supporting clinical diagnostics by quantitative measurement of the heart and adjacent vessels in cardiac MR & CT images, specifically signal intensity, distance, area, volume, and mass.
- Supporting clinical diagnostics by using area and volume for measuring cardiac function and derived parameters cardiac output and cardiac index in long axis and short axis cardiac MR & CT images.
- Flow quantifications based on velocity encoded cardiac MR images (including two and four dimensional flow analysis).
- Strain analysis of cardiac MR images by providing measurements of 2D LV myocardial function (displacement, velocity, strain, strain rate, time to peak, and torsion).
- Supporting clinical diagnostics of cardiac CT images including quantitative measurements of calcified plaques in the coronary arteries (calcium scoring), specifically Agatston and volume and mass calcium scores, visualization and quantitative measurement of heart structures including coronaries, femoral, aortic, and mitral valves.
- Evaluating CT and MR images of blood vessels. Combining digital image processing and visualization tools such as multiplanar reconstruction (MPR), thin/thick maximum intensity projection (MIP), inverted MIP thin/thick, volume rendering technique (VRT), curved planar reformation (CPR), processing tools such as bone removal (based on both single energy and dual energy) table removal and evaluation tools (vessel centerline calculation, lumen calculation, stenosis calculation) and reporting tools (lesion location, lesion characteristics) and key images. The software package is designed to support the physician in confirming the presence of physician identified lesion in blood vessels and evaluation, documentation and follow up of any such lesions.
cvi42 shall be used by qualified medical professionals, experienced in examining and evaluating cardiovascular MR or CT images, for the purpose of obtaining diagnostic information as part of a comprehensive diagnostic decision-making process. cvi42 is a software application that can be used as a stand-alone product or in a networked environment.
The target population for cvi42 and its manual workflows is not restricted; however, cvi42's semiautomated machine learning algorithms, included in the MR Function and CORE CT modules, are intended for an adult population. Further, image acquisition by a cardiac MR or CT scanner may limit the use of the software for certain sectors of the general public.
cvi42 shall not be used to view or analyze images of any part of the body except the cardiac images acquired from a cardiovascular magnetic resonance or computed tomography scanner.
Product codes (comma separated list FDA assigned to the subject device)
QIH, LLZ
Device Description
cvi42 Software Application ("cvi42") is a software as a medical device (SaMD) that is intended for evaluating CT and MR images of the cardiovascular system. Combining digital image processing, visualization, quantification, and reporting tools, cvi42 is designed to support physicians in the evaluation and analysis of cardiovascular imaging studies.
cvi42 uses machine learning techniques to aid in semi-automatic contouring of regions of interest in cardiac MR or CT images.
The data used to train these machine learning algorithms were sourced from multiple clinical sites from urban centers and from different countries. When selecting data for training, the importance of model generalization was considered and data was selected such that a good distribution of patient demographics, scanner, and image parameters were represented. The separation into training versus validation datasets is made on the study level to ensure no overlap between the two sets. As such, different scans from the same study were not split between the training and validation datasets. None of the cases used for model validation were used for training the machine learning models.
cvi42 has a graphical user interface which allows users to analyze cardiac MR & CT images qualitatively and quantitatively.
cvi42 accepts uploaded data files previously acquired by MR or CT scanners or other data collection equipment but does not interface directly with such equipment. Its functionality is independent of the type of vender acquisition equipment. The analysis results are available onscreen and can be saved with the software for future review.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
cardiovascular magnetic resonance (MR) images and computed tomography (CT) images
Anatomical Site
cardiac images, heart and adjacent vessels, coronary arteries, blood vessels
Indicated Patient Age Range
The target population for cvi42 and its manual workflows is not restricted; however, cvi42's semiautomated machine learning algorithms, included in the MR Function and CORE CT modules, are intended for an adult population.
Intended User / Care Setting
qualified medical professionals, experienced in examining and evaluating cardiovascular MR or CT images
stand-alone product or in a networked environment.
Description of the training set, sample size, data source, and annotation protocol
The data used to train these machine learning algorithms were sourced from multiple clinical sites from urban centers and from different countries. When selecting data for training, the importance of model generalization was considered and data was selected such that a good distribution of patient demographics, scanner, and image parameters were represented. The separation into training versus validation datasets is made on the study level to ensure no overlap between the two sets. As such, different scans from the same study were not split between the training and validation datasets. None of the cases used for model validation were used for training the machine learning models.
Description of the test set, sample size, data source, and annotation protocol
All data used for validation were not used during the development of the training algorithms. In general, image information for samples is anonymized and limited to ePHI-free DICOM headers and at least 50% of the data came from a U.S. population.
Across all MR and CT machine manufacturers, n = 235 anonymized patient images were used for the validation of cvi42 Auto. This translates into 70 samples for Coronary Analysis, 102 samples for Calcium analysis, 63 samples for SAX Function contouring, 63 for each of 2-CV, 3-CV, and 4CV LAX function contouring, and 252 samples for Function Classification. Image information for all samples was anonymized and limited to ePHI-free DICOM headers. At least 50% of the data came from a U.S. population.
The validation data was sourced from 9 different sites, with 90% of the data sampled from US sources. All performance testing results met Circle's pre-defined acceptance criteria.
Compared to a reference standard established from three expert readers.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Performance testing was conducted to verify compliance with specified design requirements in accordance with ISO 13485:2016, BS EN 62304:2006, ISO 14971:2019, and DICOM standards.
Verification and validation testing were conducted to ensure specifications and performance of the device and were performed per the FDA Guidance "Technical Performance Assessment of Quantitative Imaging in Radiological Device Premarket Submission". No clinical studies were necessary to support substantial equivalence.
cvi42 has been tested according to the specifications that are documented in a Master Software Test Plan. Testing is an integral part of Circle Cardiovascular Imaging Inc.'s software development as described in the company's product development process.
Validation of non-Machine Learning Outputs:
The validation of non-ML or rule-based algorithms and mathematical outputs in cvi42 is performed through general in-house software QA verification and validation process including unit tests, content/phantom tests, quantitative and qualitative analysis, and visual/manual evaluation. Some more complex algorithms, such as Strain measurement, however, have undergone additional validation to ensure the safe and effective use of the software.
Strain: 2D LV:
The tracking performance and the clinically relevant Global Longitudinal and Global Circumferential strains were validated using a complimentary combination of simple and realistic phantoms, real MRI data, and analytical solutions. The tracking performance was evaluated with simple analytical phantoms generated with variable input parameters; the deformation field generated by the strain module was evaluated on realistic phantoms with artificially imposed known deformation field and perturbations; and the performance of the constrained tissue tracking algorithm was also compared to manual tracking in ES phase by three expert readers. The computation of the deformation metrics from the tracked deformations were evaluated analytically.
Validation of Machine Learning Derived Outputs:
The machine learning algorithms of cvi42 have been trained and tested on images acquired from major vendors of MR and CT imaging devices. All data used for validation were not used during the development of the training algorithms. In general, image information for samples is anonymized and limited to ePHI-free DICOM headers and at least 50% of the data came from a U.S. population. All performance testing results have met Circle's pre-defined acceptance criteria.
cvi42 Auto: MR Function & CORE CT:
Across all MR and CT machine manufacturers, n = 235 anonymized patient images were used for the validation of cvi42 Auto. This translates into 70 samples for Coronary Analysis, 102 samples for Calcium analysis, 63 samples for SAX Function contouring, 63 for each of 2-CV, 3-CV, and 4CV LAX function contouring, and 252 samples for Function Classification. At least 50% of the data came from a U.S. population.
- For CMR function analysis, Classification accuracy was between 97 % - 100%. Volumetric MAE for SAX were between 7% - 10%, and volumetric MAE for LAX were between 5% - 9%.
- For Calcium analysis, Classification performance results were between 86% - 99%.
- For Coronary analysis, Centerline performance results were between 82% - 94%. Mask performance results were between 98% - 100%.
CORE CT: CT Function:
The validation data was sourced from 9 different sites, with 90% of the data sampled from US sources.
- Compared to a reference standard established from three expert readers, the ML-based model is capable of segmenting the LV cavity with less than 10% difference in MAE, a Dice coefficient above 86%, a HD below 9.5 mm, and an EF bias of 1.3% with a 95% confidence interval of [-12, 14].
- Similarly, the RV cavity is segmented with less than 18% MAE, a Dice coefficient above 85%, a HD below 18 mm, and an EF bias of -5.5% with a 95% confidence interval of [-15, 4.4].
- Lastly, the LV myocardium is segmented with less than 17% MAE, a Dice coefficient above 82%, and a HD below 15 mm.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
- Classification Accuracy
- True Positives (TP), True Negatives (TN), False Positives (FP), False Negatives (FN)
- Mean Absolute Error (MAE)
- 3D Hausdorff Distance (HD)
- Dice coefficient
- EF bias
Predicate Device(s): If the device was cleared using the 510(k) pathway, identify the Predicate Device(s) K/DEN number used to claim substantial equivalence and list them here in a comma separated list exactly as they appear in the text. List the primary predicate first in the list.
K082628, K111373, K141480, K213998, K232661, K241038
Reference Device(s): Identify the Reference Device(s) K/DEN number and list them here in a comma separated list exactly as they appear in the text.
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information for the subject device only (e.g. presence / absence, what scope was granted / cleared under the PCCP, any restrictions, etc).
Not Found
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).
0
Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). On the left is the seal of the Department of Health & Human Services. To the right of the seal is the FDA logo in blue, with the words "U.S. FOOD & DRUG" on one line and "ADMINISTRATION" on the line below. The logo is simple and professional, and it is easily recognizable.
Circle Cardiovascular Imaging Inc. Omar Naimi Regulatory Affairs Analyst Suite 1800, 707 8 Avenue SW Calgary, AB T2P 1H5 Canada
Re: K242781
October 15, 2024
Trade/Device Name: cvi42 Software Application Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: QIH, LLZ Dated: September 13, 2024 Received: September 16, 2024
Dear Omar Naimi:
We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device"
1
(https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (OS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-device-advicecomprehensive-regulatory-assistance/unique-device-identification-system.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatory
2
assistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
Jessica Lamb
Jessica Lamb, Ph.D. Assistant Director DHT8B: Division of Radiological Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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Indications for Use
Submission Number (if known)
K242781
Device Name
cvi42 Software Application
Indications for Use (Describe)
cvi42 is intended to be used for viewing, post-processing, qualitative and quantitative evaluation of cardiovascular magnetic resonance (MR) images and computed tomography (CT) images in a Digital Imaging and Communications in Medicine (DICOM) Standard format.
lt enables:
· Importing cardiac MR & CT Images in DICOM format.
• Supporting clinical diagnostics by qualitative analysis of cardiac MR & CT images using display functionality such as panning, windowing, zooming, navigation through series/slices and phases, 3D reconstruction of images including multiplanar reconstructions of the images.
• Supporting clinical diagnostics by quantitative measurement of the heart and adjacent vessels in cardiac MR & CT images, specifically signal intensity, distance, area, volume, and mass.
• Supporting clinical diagnostics by using area and volume for measuring cardiac function and derived parameters cardiac output and cardiac index in long axis and short axis cardiac MR & CT images.
• Flow quantifications based on velocity encoded cardiac MR images (including two and four dimensional flow analysis).
• Strain analysis of cardiac MR images by providing measurements of 2D LV myocardial function (displacement, velocity, strain, strain rate, time to peak, and torsion).
· Supporting clinical diagnostics of cardiac CT images including quantitative measurements of calcified plaques in the coronary arteries (calcium scoring), specifically Agatston and volume and mass calcium scores, visualization and quantitative measurement of heart structures including coronaries, femoral, aortic, and mitral valves.
· Evaluating CT and MR images of blood vessels. Combining digital image processing and visualization tools such as multiplanar reconstruction (MPR), thin/thick maximum intensity projection (MIP), inverted MIP thin/thick, volume rendering technique (VRT), curved planar reformation (CPR), processing tools such as bone removal (based on both single energy and dual energy) table removal and evaluation tools (vessel centerline calculation, lumen calculation, stenosis calculation) and reporting tools (lesion location, lesion characteristics) and key images. The software package is designed to support the physician in confirming the presence of physician identified lesion in blood vessels and evaluation, documentation and follow up of any such lesions.
cvi42 shall be used by qualified medical professionals, experienced in examining and evaluating cardiovascular MR or CT images, for the purpose of obtaining diagnostic information as part of a comprehensive diagnostic decision-making process. cvi42 is a software application that can be used as a stand-alone product or in a networked environment.
The target population for cvi42 and its manual workflows is not restricted; however, cvi42's semiautomated machine learning algorithms, included in the MR Function and CORE CT modules, are intended for an adult population. Further, image acquisition by a cardiac MR or CT scanner may limit the use of the software for certain sectors of the general public.
4
cvi42 shall not be used to view or analyze images of any part of the body except the cardiac images acquired from a cardiovascular magnetic resonance or computed tomography scanner.
Type of Use (Select one or both, as applicable)
Prescription Use (Part 21 CFR 801 Subpart D)
Over-The-Counter Use (21 CFR 801 Subpart C)
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Image /page/5/Picture/2 description: The image shows the logo for Circle Cardiovascular Imaging. The logo features a stylized green and yellow circle above the word "circle" in gray lowercase letters. Below "circle" are the words "CARDIOVASCULAR IMAGING" in smaller, gray, uppercase letters.
The following 510(k) summary of safety and effectiveness information is submitted in accordance with the requirements of the Safe Medical Device Act 1990 and 21 CFR 807.92(c).
l. SUBMITTER
| Submitter's Name: | Circle Cardiovascular Imaging, Inc. |
|---|---|
| Address: | Suite 1800 – 707 8th Ave SW, Calgary, AB, Canada, T2P 1H5 |
| Date Prepared: | October 11 2024 |
| Telephone Number: | +1 587-686-0784 |
| Contact Person : | Omar Naimi |
| Email: | omar.naimi@circlecvi.com |
ll. DEVICE
| 510(k): | K242781 |
|---|---|
| Name of the Device: | cvi42 Software Application |
| Short Brand Name: | cvi42 |
| Common or Usual Name: | Automated Radiological Image Processing Software |
| Classification Name: | Medical image management and processing system |
| Proposed Classification: | Device Class: II |
| Product Codes: QIH, LLZ | |
| Regulation Number: 21 CFR 892.2050 |
���. PREDICATE DEVICE
The primary predicate is cmr2 under K082628, and the additional predicates are ct42 under K111373, cvi42 vascular add-on under K141480, cvi42 Auto under K213998, Strain Module under 232661, and CT Function under 241038. Each of the predicate devices are manufactured by Circle Cardiovascular Imaging Inc.
The predicate devices have not been subject to a design-related recall.
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IV. DEVICE DESCRIPTION
cvi42 Software Application ("cvi42") is a software as a medical device (SaMD) that is intended for evaluating CT and MR images of the cardiovascular system. Combining digital image processing, visualization, quantification, and reporting tools, cvi42 is designed to support physicians in the evaluation and analysis of cardiovascular imaqing studies.
cvi42 uses machine learning techniques to aid in semi-automatic contouring of regions of interest in cardiac MR or CT images.
The data used to train these machine learning algorithms were sourced from multiple clinical sites from urban centers and from different countries. When selecting data for training, the importance of model generalization was considered and data was selected such that a good distribution of patient demographics, scanner, and image parameters were represented. The separation into training versus validation datasets is made on the study level to ensure no overlap between the two sets. As such, different scans from the same study were not split between the training and validation datasets. None of the cases used for model validation were used for training the machine learning models.
cvi42 has a graphical user interface which allows users to analyze cardiac MR & CT images qualitatively and quantitatively.
cvi42 accepts uploaded data files previously acquired by MR or CT scanners or other data collection equipment but does not interface directly with such equipment. Its functionality is independent of the type of vender acquisition equipment. The analysis results are available onscreen and can be saved with the software for future review.
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| Measurement [units] | Description | Application |
|---|---|---|
| Distance [mm] | Length between two points, for both | |
| curved lines (splines) and straight lines, | ||
| including the diameter (including min, | ||
| max, average) resulting from closed | ||
| splines and depth | Diameter & depth of cardiovascular | |
| structures of interest | ||
| Perimeter [mm] | The perimeter of a contour (closed spline) | Perimeter of cardiovascular structures of |
| interest | ||
| Area [cm²] | The area within contour(s) | Area of cardiovascular structures of interest |
| Signal intensity [HU] | ||
| (modality CT) / Intensity | ||
| [unitless] (modality MR) | Modality CT: Hounsfield value (in | |
| Hounsfield Units, HU) of the underlying | ||
| pixels | ||
| Modality MR: Intensity / shade of grey | ||
| (high, intermediate, low) of underlying | ||
| pixels | Intensity of pixels in cardiovascular | |
| structures of interest | ||
| Volume [mm³ or mL] | The volume within contour(s) | Volume of cardiovascular structures of |
| interest | ||
| Coordinates [mm, mm, mm] | Location in the x-, y-, and z-planes of a | |
| point | Coordinates of points of interest on a 3D | |
| rendering, for export purposes | ||
| Mass [g] | The mass within contour(s) | Mass of cardiovascular structures of interest |
| Displacement [mm or | ||
| degree] | The displacement vector represents the | |
| position of a point with respect to the | ||
| position of that point in the reference (end | ||
| diastole) phase. | Strain within cardiovascular structures of | |
| interest (e.g., myocardium) | ||
| Agatston Score [HU] | Industry-standard measure for coronary | |
| calcium based on volume and intensity of | ||
| calcified plaque | For assessing overall calcified plaque | |
| burden in coronary arteries. | ||
| Angle [degrees] | The angle of an object/structure of | |
| interest | Angle between two lines of interest | |
| Stenosis [%] | The narrowing of a vessel in area or | |
| diameter compared to a normal reference | ||
| location | For measuring an abnormal narrowing in an | |
| artery | ||
| Velocity [mL/min or cm/s] | The velocity of moving objects within | |
| contour(s) | Velocity within cardiovascular structures of | |
| interest (e.g., blood flow) | ||
| Strain [%] | Strain is a measure of the deformation in | |
| shape and dimension of the heart muscle | ||
| during the cardiac cycle. | Strain within cardiovascular structures of | |
| interest (e.g., myocardium) | ||
| Strain Rate [1/s] | Derivative of strain with respect to time | Strain within cardiovascular structures of |
| interest, as above | ||
| Time to Peak [ms] | Trigger time elapsed from the first phase | |
| till the phase where the peak strain has | ||
| been reached. | Strain within cardiovascular structures of | |
| interest, as above | ||
| Torsion [degree/cm] | The difference in rotation between the | |
| apical and basal slices divided by the | ||
| apical and basal slices. Note | ||
| circumferential displacement represents | ||
| an angle. | Strain within cardiovascular structures of | |
| interest, as above | ||
| End Diastolic Volume [mL] | LV/RV cavity volume at the phase | |
| defined as the ED | Calculated clinical data for LV/RV | |
| End Systolic Volume [mL] | LV/RV cavity volume at the phase | |
| defined as the ES | Calculated clinical data for LV/RV | |
| Stroke Volume [mL] | Stroke volume is the volume of blood | |
| pumped out of the LV/RV during each | ||
| cardiac contraction and is represented by | ||
| the difference of EDV and ESV. | Calculated clinical data for LV/RV | |
| Ejection Fraction [%] | Ejection fraction is measured as a | |
| percentage of the total amount of blood in | ||
| LV/RV that is pumped out with each | ||
| cardiac cycle. It is calculated by dividing | ||
| the SV by EDV. | Calculated clinical data for LV/RV | |
| Cardiac Output [L/min] | Cardiac output is the amount of blood | |
| pumped by the heart in a minute and is | ||
| calculated by multiplying the SV with | ||
| heart rate per minute. | Calculated clinical data for LV/RV | |
| Cardiac Index [L/min/m²] | Cardiac index is a hemodynamic | |
| parameter that relates the CO from LV in | ||
| one minute to BSA and is obtained by | ||
| dividing the CO by BSA. | Calculated clinical data for LV | |
| End Diastolic Mass [g] | LV myocardial mass at the phase defined | |
| as the ED and is calculated by multiplying | ||
| the myocardial volume in ED phase with | ||
| myocardial density (1.05 g/ml). | Calculated clinical data for LV | |
| End Systolic Mass [g] | LV myocardial mass at the phase defined | |
| as the ES and is calculated by multiplying | ||
| the myocardial volume in ES phase with | ||
| myocardial density (1.05 g/ml). | Calculated clinical data for LV | |
| Body Surface Area [m²] | The total surface area of the body | Surface area of the patient body used in |
| medical indicators or assessments |
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V. INTENDED USE / INDICATIONS FOR USE
Intended Use
cvi42 is intended to be used by qualified medical professionals for viewing, post-processing and quantitative evaluation of cardiovascular magnetic resonance (MR) images and cardiovascular computed tomography (CT) images in a Digital Imaging and Communications in Medicine Standard format, for the purpose of obtaining diagnostic information as part of a comprehensive diaqnostic decision-making process
Indications for Use
cvi42 is intended to be used for viewing, post-processing, qualitative evaluation of cardiovascular magnetic resonance (MR) images and computed tomography (CT) images in a Digital Imaging and Communications in Medicine (DICOM) Standard format.
lt enables:
- . Importing cardiac MR & CT Images in DICOM format.
- . Supporting clinical diagnostics by qualitative analysis of cardiac MR & CT images using display functionality such as panning, windowing, zooming, navigation through series/slices and phases, 3D reconstruction of images including multiplanar reconstructions of the images.
- . Supporting clinical diagnostics by quantitative measurement of the heart and adjacent vessels in cardiac MR & CT images, specifically signal intensity, distance, area, volume, and mass.
- . Supporting clinical diagnostics by using area and volume for measuring cardiac function and derived parameters cardiac output and cardiac index in long axis and short axis cardiac MR & CT images.
- . Flow quantifications based on velocity encoded cardiac MR images (including two and four dimensional flow analysis).
- . Strain analysis of cardiac MR images by providing measurements of 2D LV myocardial function (displacement, velocity, strain, strain rate, time to peak, and torsion).
- . Supporting clinical diagnostics of cardiac CT images including quantitative measurements of calcified plaques in the coronary arteries (calcium scoring), specifically Agatston and volume and mass calcium scores, visualization and quantitative measurement of heart structures including coronaries, femoral, aortic, and mitral valves.
- . Evaluating CT and MR images of blood vessels. Combining digital image processing and visualization tools such as multiplanar reconstruction (MPR), thin/thick maximum intensity projection (MIP), inverted MIP thin/thick, volume rendering technique (VRT), curved planar reformation (CPR), processing tools such as bone removal (based on both single energy and dual energy) table removal and evaluation tools (vessel centerline calculation, lumen calculation, stenosis calculation) and reporting tools (lesion location, lesion characteristics) and key images. The software package is designed to support the
10
physician in confirming the presence or absence of physician identified lesion in blood vessels and evaluation, documentation and follow up of any such lesions.
cvi42 shall be used by qualified medical professionals, experienced in examining and evaluating cardiovascular MR or CT images, for the purpose of obtaining diagnostic information as part of a comprehensive diagnostic decision-making process. cvi42 is a software application that can be used as a stand-alone product or in a networked environment.
The target population for cvi42 and its manual workflows is not restricted; however, cvi42's semiautomated machine learning algorithms, included in the MR Function and CORE CT modules, are intended for an adult population. Further, image acquisition by a cardiac MR or CT scanner may limit the use of the software for certain sectors of the general public.
cvi42 shall not be used to view or analyze images of any part of the body except the cardiac images acquired from a cardiovascular magnetic resonance or computed tomography scanner.
VI. COMPARISON WITH PREDICATE DEVICE
The detailed analysis of the subject device and the predicate device (shown in Table 2 and Table 3) demonstrates that the subject device is substantially equivalent in indications for use / intended use, technological characteristics, functionality, and operating principles with the predicates (K092628, K111373, K141480, K213998, K232661, and K241038). Of the three characteristics (technical, biological, and clinical) required for the demonstration of equivalence, biological characteristics are not applicable since both the subject device and predicate device are software as a medical device application with no tangible component interfacing with the body.
11
| Table 2. Subject Device Intended Use / Indications for Use | |
|---|---|
| ------------------------------------------------------------ | -- |
| | Subject Device | | Primary Predicate
cmr42 (K082628) | Predicate
ct42 (K111373) | Predicate
cvi42 (K141480) | Predicate
cvi42 Auto (K213998) | Predicate
Strain (K232661) | Predicate
CT Function (K241038) |
|---------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| | cvi42 Software Application (K242781) | | Manufactured by Circle | Manufactured by Circle | Manufactured by Circle | Manufactured by Circle | Manufactured by Circle | Manufactured by Circle |
| | Manufactured by Circle | Intended Use | Viewing, post-processing,
qualitative and quantitative
evaluation of cardiovascular MR
images in DICOM format. | Viewing, post-processing, qualitative
and quantitative evaluation of
cardiovascular CT images in DICOM
format. | Viewing, post-processing, qualitative
and quantitative evaluation of blood
vessels and cardiovascular MR and
CT images in DICOM format. | Viewing, post-processing, qualitative
and quantitative evaluation of blood
vessels and cardiovascular MR and
CT images in DICOM format. | The Myocardial Strain Software
Application is intended for qualitative
and quantitative evaluation of
cardiovascular MR images in a
DICOM Standard format. As
perquisite, the user confirms
endocardial and epicardial contours in
a reference phase, and the software
tracks features over the cardiac cycle
and computed 2D myocardial
deformation and movement (e.g.,
strain, displacement, velocity). | The Cardiac CT Function Software
Application is intended for qualitative
and quantitative evaluation of
cardiovascular CT images in a DICOM
Standard format, to calculate and
display cardiac function metrics (e.g.,
end diastolic volume, end systolic
volume, stroke volume, ejection fraction
cardiac output, cardiac index, and LV
myocardial mass). |
| Intended Use | cvi42 is intended to be used by qualified medical professionals for viewing, post-processing and quantitative evaluation of cardiovascular magnetic resonance (MR) images and cardiovascular computed tomography (CT) images in a Digital Imaging
and Communications in Medicine Standard format, for the purpose of obtaining diagnostic information as part of a comprehensive diagnostic decision-making process | Indications for Use | cmr42 is intended to be used for
viewing, post-processing and
quantitative evaluation of
cardiovascular magnetic resonance
(MR) images in a Digital Imaging
and Communications in Medicine
(DICOM) Standard format.
It enables;
• Importing Cardiac MR Images in
DICOM format
• Supporting clinical diagnostics by
qualitative analysis of the cardiac
MR images using display
functionality such as panning,
windowing, zooming, navigation
through series/slices and phases.
• Supporting clinical diagnostics by
quantitative measurement of the
heart and adjacent vessels in
cardiac MR images, specifically
distance, area, volume and mass
• Supporting clinical diagnostics by
using area and volume
measurements for measuring LV
function and derived parameters
cardiac output and cardiac index in
long axis and short axis cardiac MR
images.
• Flow quantifications based on
velocity encodes images | ct42 is intended to be used for viewing,
post-processing and quantitative
evaluation of cardiovascular computed
tomography (CT) images in a Digital
Imaging and Communications in
Medicine (DICOM) Standard format.
It enables:
• Importing Cardiac CT Images in
DICOM format
• Supporting clinical diagnostics by
qualitative analysis of the cardiac CT
images using display functionality
such as panning, windowing,
zooming, navigation through
series/slices and phases, 3D
reconstruction of images including
multi-lanner reconstructions of the
images.
• Supporting clinical diagnostics by
quantitative measurement of the heart
and adjacent vessels in cardiac CT
images, specifically distance, area,
volume and mass
• Supporting clinical diagnostics by
using area and volume measurements
for measuring LV function and derived
parameters cardiac output and cardiac
index in long axis and short axis
cardiac CT images. | cvi42 vascular analysis add-on is an
image analysis software package add-
on for evaluating CT and MR images
of blood vessels. Combining digital
image processing and visualization
tools such as multiplanar
reconstruction (MPR), thin/think
maximum intensity projection (MIP)
thin and think, inverted MIP thin and
think, volume rendering technique
(VRT), curved planner reformation,
processing tools such as bone
removal (based on both single energy
and dual energy) table removal and
evaluation tools (vessel centerline
calculation, lumen calculation,
stenosis calculation) and reporting
tools (lesion location, lesion
characteristics) and key images), the
software package is designed to
support the physician in conforming
the presence or absence of physician
identified lesion in blood vessels and
evaluation, documentation and follow
up of any such lesions.
It shall be used by qualified medical
professionals, experienced in
examining and evaluating
cardiovascular CT or MR images, for
the purpose of obtaining diagnostic | cvi42 Auto is intended to be used for
viewing, post-processing, qualitative
and quantitative evaluation of
cardiovascular magnetic resonance
(MR) and computed tomography (CT)
images in a Digital Imaging and
Communications in Medicine (DICOM)
Standard format.
It enables a set of tools to assist
physicians in qualitative assessment
of cardiac images and quantitative
measurements of the heart and
adjacent vessels; perform calcium
scoring; and to confirm the presence
or absence of physician-identified
lesion in blood vessels.
The target population for cvi42 Auto's
manual workflows is not restricted;
however, cvi42 Auto's semi-
automated machine learning
algorithms are intended for an adult
population.
cvi42 Auto shall be used only for
cardiac images acquired from an MR
or CT scanner. It shall be used by
qualified medical professionals,
experienced in examining and
evaluating cardiovascular MR or CT | The Myocardial Strain Software
Application is intended for qualitative
and quantitative evaluation of
cardiovascular magnetic resonance
(CMR) images. It provides
measurements of 2D LV myocardial
function (displacement, velocity,
strain, strain rate, time to peak, and
torsion); these measurements are
used by qualified medical
professionals, experiences in
examining and evaluating CMR
images, for the purpose of obtaining
diagnostic information for patients with
suspected heart disease as part of a
comprehensive diagnostic decision-
making process. | The Cardiac CT Function Software
Application is indicated to be use with
multi-phase, multi-slice cardiovascular
CT angiography images to assist
qualified medical professionals in
assessing and evaluating cardiac
function. CT Function includes manual
and semi-automatic heart segmentation
of 2 chambers (LV and RV) and
calculation of cardiac function metrics
including end diastolic volume, end
systolic volume, stroke volume, ejection
fraction, cardiac output, cardiac index,
and LV myocardial mass. |
| Indications for Use | cvi42 is intended to be used for viewing, post-processing, qualitative and quantitative evaluation of cardiovascular magnetic resonance (MR) images and computed tomography (CT) images in a Digital Imaging and Communications in Medicine
(DICOM) Standard format. | | | | | | | |
| | It enables:
Importing cardiac MR & CT Images in DICOM format. Supporting clinical diagnostics by qualitative analysis of cardiac MR & CT images using display functionality such as panning, windowing, zooming, navigation through series/slices and phases, 3D reconstruction of images including multiplanar reconstructions of the images. Supporting clinical diagnostics by quantitative measurement of the heart and adjacent vessels in cardiac MR & CT images, specifically signal intensity, distance, area, volume, and mass. Supporting clinical diagnostics by using area and volume for measuring cardiac function and derived parameters cardiac output and cardiac index in long axis and short axis cardiac MR & CT images. Flow quantifications based on velocity encoded cardiac MR images (including two and four dimensional flow analysis). Strain analysis of cardiac MR images by providing measurements of 2D LV myocardial function (displacement, velocity, strain, strain rate, time to peak, and torsion). Supporting clinical diagnostics of cardiac CT images including quantitative measurements of calcified plaques in the coronary arteries (calcium scoring), specifically Agatston and volume and mass calcium scores, visualization and quantitative measurement of heart structures including coronaries, femoral, aortic, and mitral valves. Evaluating CT and MR images of blood vessels. Combining digital image processing and visualization tools such as multiplanar reconstruction (MPR), thin/thick maximum intensity projection (MIP), inverted MIP thin/thick, volume rendering technique (VRT), curved planar reformation (CPR), processing tools such as bone removal (based on both single energy and dual energy) table removal and evaluation tools (vessel centerline calculation, lumen calculation, stenosis calculation) and reporting tools (lesion location, lesion characteristics) and key images. The software package is designed to support the physician in confirming the presence or absence of physician identified lesion in blood vessels and evaluation, documentation and follow up of any such lesions. cvi42 shall be used by qualified medical professionals, experienced in examining and evaluating cardiovascular MR or CT images, for the purpose of obtaining diagnostic information as part of a comprehensive diagnostic decision-making process.
cvi42 is a software application that can be used as a stand-alone product or in a networked environment.
The target population for cvi42 and its manual workflows is not restricted; however, cvi42's semi-automated machine learning algorithms, included in the MR Function and CORE CT modules, are intended for an adult population. Further, image acquisition by a cardiac MR or CT scanner may limit the use of the software for certain sectors of the general public.
cvi42 shall not be used to view or analyze images of any part of the body except the cardiac images acquired from a cardiovascular magnetic resonance or computed tomography scanner. | | | | | | | |
12
Table 3. Predicate Device Intended Use / Indications for Use
Circle Cardiovascular Imaging Inc.
13
| Primary Predicate | Predicate | Predicate | Predicate | Predicate | Predicate |
|---|---|---|---|---|---|
| cmr42 (K082628) | ct42 (K111373) | cvi42 (K141480) | cvi42 Auto (K213998) | Strain (K232661) | CT Function (K241038) |
| Manufactured by Circle | Manufactured by Circle | Manufactured by Circle | Manufactured by Circle | Manufactured by Circle | Manufactured by Circle |
| It shall be used by qualified medical | |||||
| professionals, experienced in | |||||
| examining and evaluating | |||||
| cardiovascular MR images, for the | |||||
| purpose of obtaining diagnostic | |||||
| information as part of a | |||||
| comprehensive diagnostic decision- | |||||
| making process. cmr42 is a software | |||||
| application that can be used as a | |||||
| stand-alone product or in a | |||||
| networked environment. |
The target population for the cmr42
is not restricted, however the image
acquisition by a cardiac magnetic
resonance scanner may limit the
use of the device for certain sectors
of the general public.
cmr42 shall not be used to view or
analyze images of any part of the
body except the cardiac magnetic
resonance images acquired from a
cardiovascular magnetic resonance
scanner. | • Supporting clinical diagnostics by
quantitative measurements of calcified
plaques in the coronary arteries
(calcium scoring), specifically
Agatston and volume and mass
calcium scores
It shall be used by qualified medical
professionals, experienced in
examining and evaluating
cardiovascular CT images, for the
purpose of obtaining diagnostic
information as part of a
comprehensive diagnostic decision-
making process. ct42 is a software
application that can be used as a
stand-alone product or in a networked
environment.
The target population for the ct42 is not
restricted, however the image
acquisition by a cardiac CT scanner
may limit the use of the device for
certain sectors of the general public.
ct42 shall not be used to view or
analyze images of any part of the
body except the cardiac CT images
acquired from a cardiovascular CT
scanner. | information as part of a
comprehensive diagnostic decision-
making process. cvi42 is a software
application that can be used as a
stand-alone product or in a networked
environment.
The target population for the cvi42 is
not restricted. | images, for the purpose of obtaining
diagnostic information as part of a
comprehensive diagnostic decision-
making process. | | |
14
| Table 3. Regulatory and technological features comparison. | |||||||
|---|---|---|---|---|---|---|---|
| Feature | Subject Device | ||||||
| cvi42 Software Application | |||||||
| (K242781) | |||||||
| Manufactured by Circle | Primary Predicate | ||||||
| cmr42 (K082628) | |||||||
| Manufactured by Circle | Predicate | ||||||
| ct42 (K111373) | |||||||
| Manufactured by Circle | Predicate | ||||||
| cvi42 (K141480) | |||||||
| Manufactured by Circle | Predicate | ||||||
| cvi42 Auto (K213998) | |||||||
| Manufactured by Circle | Predicate | ||||||
| Strain (K232661) | |||||||
| Manufactured by Circle | Predicate | ||||||
| CT Function (K241038) | |||||||
| Manufactured by Circle | |||||||
| Device Class | II | II | II | II | II | II | II |
| Device Classification | QIH, LLZ | LLZ | LLZ | LLZ | QIH, LLZ | LLZ | QIH, LLZ |
| Regulation Name | Medical image management | ||||||
| and processing system | Picture Archiving and | ||||||
| Communications System | Picture Archiving and | ||||||
| Communications System | Picture Archiving and | ||||||
| Communications System | Medical image management | ||||||
| and processing system | Medical image management | ||||||
| and processing system | Medical image management | ||||||
| and processing system | |||||||
| Regulation Number | 21 CFR 892.2050 | 21 CFR 892.2050 | 21 CFR 892.2050 | 21 CFR 892.2050 | 21 CFR 892.2050 | 21 CFR 892.2050 | 21 CFR 892.2050 |
| Imaging Modalities | MR and CT | MR | CT | MR and CT | MR and CT | MR | CT |
| DICOM Compliant | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Import and display MR/CT | |||||||
| images | Yes | Yes (MR only) | Yes (CT only) | Yes | Yes | Yes (MR only) | Yes (CT only) |
| Post process CMR/CCT images | Yes | Yes (MR only) | Yes (CT only) | Yes | Yes | Yes (MR only) | Yes (CT only) |
| Images can be displayed by | |||||||
| study and series | Yes | Yes | N/A | N/A | N/A | N/A | N/A |
| Store images | Yes | Yes | N/A | N/A | N/A | N/A | N/A |
| 2D Imaging | Yes | Yes | N/A | N/A | N/A | N/A | N/A |
| 3D Imaging | Yes | No | Yes | Yes | Yes | Yes | Yes |
| Multiplanar Reformat (MPR) | Yes | No | Yes | Yes | Yes | No | Yes |
| Navigation Tools | Panning, | ||||||
| Windowing, | |||||||
| Zooming, | |||||||
| Series/slices and phases | Panning, | ||||||
| Windowing, | |||||||
| Zooming | |||||||
| Series/slices and phases | N/A | N/A | N/A | N/A | N/A | ||
| Measurements | Distance | ||||||
| Perimeter | |||||||
| Area | |||||||
| Signal Intensity | |||||||
| Volume | |||||||
| Coordinates | |||||||
| Mass | |||||||
| Displacement | |||||||
| Agatston Score | |||||||
| Angle | |||||||
| Stenosis | |||||||
| Velocity | |||||||
| Strain | |||||||
| Strain Rate | |||||||
| Time to Peak | |||||||
| Torsion | |||||||
| End Diastolic Volume (EDV) | |||||||
| End Systolic Volume (ESV) | |||||||
| Stroke Volume (SV) | |||||||
| Ejection Fraction (EF) | |||||||
| Cardiac Output (CO) | Distance | ||||||
| Perimeter | |||||||
| Area | |||||||
| Signal Intensity | |||||||
| Volume | |||||||
| Mass | |||||||
| Coordinates | Distance | ||||||
| Perimeter | |||||||
| Area | |||||||
| Signal Intensity | |||||||
| Volume | |||||||
| Coordinates | |||||||
| Agatston Score | Distance | ||||||
| Perimeter | |||||||
| Area | |||||||
| Signal Intensity | |||||||
| Volume | |||||||
| Coordinates | |||||||
| Angle | |||||||
| Stenosis | Distance | ||||||
| Perimeter | |||||||
| Area | |||||||
| Signal Intensity | |||||||
| Volume | |||||||
| Agatston Score | |||||||
| Stenosis | |||||||
| End Diastolic Volume (EDV) | |||||||
| End Systolic Volume (ESV) | |||||||
| Stroke Volume (SV) | |||||||
| Ejection Fraction (EF) | |||||||
| Cardiac Output (CO) | |||||||
| End Diastolic Mass (EDV) | |||||||
| End Systolic Mass (ESV) | |||||||
| Body Surface Area (BSA) | Displacement | ||||||
| Velocity | |||||||
| Strain | |||||||
| Strain Rate | |||||||
| Time to Peak | |||||||
| Torsion | End Diastolic Volume (EDV) | ||||||
| End Systolic Volume (ESV) | |||||||
| Stroke Volume (SV) | |||||||
| Ejection Fraction (EF) | |||||||
| Cardiac Output (CO) | |||||||
| Cardiac Index (CI) | |||||||
| End Diastolic Mass (EDM) | |||||||
| End Systolic Mass (ESM) | |||||||
| Body Surface Area (BSA) | |||||||
| Feature | Subject Device | ||||||
| cvi42 Software Application | |||||||
| (K242781) | |||||||
| Manufactured by Circle | Primary Predicate | ||||||
| cmr42 (K082628) | |||||||
| Manufactured by Circle | Predicate | ||||||
| ct42 (K111373) | |||||||
| Manufactured by Circle | Predicate | ||||||
| cvi42 (K141480) | |||||||
| Manufactured by Circle | Predicate | ||||||
| cvi42 Auto (K213998) | |||||||
| Manufactured by Circle | Predicate | ||||||
| Strain (K232661) | |||||||
| Manufactured by Circle | Predicate | ||||||
| CT Function (K241038) | |||||||
| Manufactured by Circle | |||||||
| Cardiac Index (CI) | |||||||
| End Diastolic Mass (EDM) | |||||||
| End Systolic Mass (ESM) | |||||||
| Body Surface Area (BSA) | |||||||
| Quantitative assessment of | |||||||
| cardiac function | Manual segmentation, and | ||||||
| semi-automatic segmentation | |||||||
| using Machine Learning | |||||||
| technique of four heart | |||||||
| chambers in long and short- | |||||||
| axis views | Manual segmentation of four | ||||||
| heart chambers in long and | |||||||
| short-axis views | Manual segmentation, and | ||||||
| semi-automatic segmentation | |||||||
| of four heart chambers in short- | |||||||
| axis views | Manual segmentation, and | ||||||
| semi-automatic segmentation | |||||||
| of four heart chambers in long | |||||||
| and short-axis views | Manual segmentation, and | ||||||
| semi-automatic segmentation | |||||||
| using Machine Learning | |||||||
| technique of four heart | |||||||
| chambers in long and short- | |||||||
| axis views | Manual segmentation, 2D | ||||||
| functional analysis of | |||||||
| myocardial deformation | Semi-automatic determination | ||||||
| of epicardial and endocardial | |||||||
| contours, via segmentation of | |||||||
| the LV cavity, LV myocardium, | |||||||
| and RV cavity and the ED and | |||||||
| ES phases using Machine | |||||||
| Learning Techniques | |||||||
| Assessment of cardiac blood flow | Quantification of blood flow | ||||||
| using MR velocity encoded | |||||||
| images. | Quantification of blood flow | ||||||
| using MR velocity encoded | |||||||
| images. | N/A | N/A | N/A | N/A | N/A | ||
| Centerline placement in coronary | |||||||
| vessels | Manual and semi-automatic | ||||||
| using Machine Learning | |||||||
| technique | Manual | Manual and semi-automatic | Manual and semi-automatic | Manual and semi-automatic | |||
| using Machine Learning | |||||||
| technique | No | No | |||||
| Calcium Scoring | Yes, using ML methodology | No | Yes, using non-ML | ||||
| methodology | No | Yes, using ML methodology | No | No | |||
| Workstation operating system | macOS, | ||||||
| Microsoft Windows | macOS, | ||||||
| Microsoft Windows | macOS, | ||||||
| Microsoft Windows | macOS, | ||||||
| Microsoft Windows | macOS, | ||||||
| Microsoft Windows | macOS, | ||||||
| Microsoft Windows | macOS, | ||||||
| Microsoft Windows |
Circle Cardiovascular Imaging Inc.
Non-Confidential
15
NOTE: Some items have been marked Not Applicatity is covered via other predicate devices in which the subject device is being ompared to.
16
PERFORMANCE DATA AND TESTING VII.
Performance testing was conducted to verify compliance with specified design requirements in accordance with ISO 13485:2016, BS EN 62304:2006, ISO 14971:2019, and DICOM standards.
Verification and validation testing were conducted to ensure specifications and performance of the device and were performed per the FDA Guidance "Technical Performance Assessment of Quantitative Imaging in Radiological Device Premarket Submission". No clinical studies were necessary to support substantial equivalence.
cvi42 has been tested according to the specifications that are documented in a Master Software Test Plan. Testing is an integral part of Circle Cardiovascular Imaging Inc.'s software development as described in the company's product development process.
Validation of non-Machine Learning Outputs
The validation of non-ML or rule-based algorithms and mathematical outputs in cvi42 is performed through general in-house software QA verification and validation process including unit tests, content/phantom tests, quantitative and qualitative analysis, and visual/manual evaluation. Some more complex algorithms, such as Strain measurement, however, have undergone additional validation to ensure the safe and effective use of the software.
Strain: 2D LV
The tracking performance and the clinically relevant Global Longitudinal and Global Circumferential strains were validated using a complimentary combination of simple and realistic phantoms, real MRI data, and analytical solutions. The tracking performance was evaluated with simple analytical phantoms generated with variable input parameters; the deformation field generated by the strain module was evaluated on realistic phantoms with artificially imposed known deformation field and perturbations; and the performance of the constrained tissue tracking algorithm was also compared to manual tracking in ES phase by three expert readers. The computation of the deformation metrics from the tracked deformations were evaluated analytically.
17
Validation of Machine Learning Derived Outputs
The machine learning algorithms of cvi42 have been trained and tested on images acquired from major vendors of MR and CT imaging devices. All data used for validation were not used during the development of the training algorithms. In general, image information for samples is anonymized and limited to ePHI-free DICOM headers and at least 50% of the data came from a U.S. population. All performance testing results have met Circle's pre-defined acceptance criteria.
cvi42 Auto: MR Function & CORE CT
The machine learning algorithms of cvi42 Auto (MR-CMR Function, CORE CT Coronary, and CORE CT-Calcium) have been trained and tested on images acquired from major vendors of MR and CT imaging devices. All data used for validation were not used during the development of the training algorithms.
Across all MR and CT machine manufacturers, n = 235 anonymized patient images were used for the validation of cvi42 Auto. This translates into 70 samples for Coronary Analysis, 102 samples for Calcium analysis, 63 samples for SAX Function contouring, 63 for each of 2-CV, 3-CV, and 4CV LAX function contouring, and 252 samples for Function Classification. Image information for all samples was anonymized and limited to ePHI-free DICOM headers. At least 50% of the data came from a U.S. population.
All performance testing results met Circle's pre-defined acceptance criteria.
- For CMR function analysis, the performance acceptance criteria were pre-defined to . evaluate the performance of the ML model based on classification accuracy defined by true positives (TP), true negatives (TN), false positives (FP), and false negatives (FN). Mean volume prediction error (Mean Absolute Error, or MAE) was also calculated. Series classification performance results were between 97 % - 100%. Volumetric MAE for SAX were between 7% - 10%, and volumetric MAE for LAX were between 5% - 9%.
- For Calcium analysis, the performance acceptance criteria were pre-defined to evaluate . the performance of the ML model based on classification accuracy defined by TP. TN. FP. and FN. Classification performance results were between 86% - 99%.
- For Coronary analysis, the performance acceptance criteria were pre-defined to evaluate . the centerline quality and performance (based on TP and FN), and success rate for relevant masks. Centerline performance results were between 82% - 94%. Mask performance results were between 98% - 100%.
CORE CT: CT Function
The Machine Learning (ML) algorithms of the CT Function Module have been trained and tested on images acquired from major vendors of CT imaging devices. All data used for validation were not used during the development of the ML algorithms. Image information for all samples was anonymized and limited to ePHI-free DICOM headers. The validation data was sourced from 9 different sites, with 90% of the data sampled from US sources. All performance testing results met Circle's pre-defined acceptance criteria.
For cardiac CT function analysis, the acceptance criteria were pre-defined to evaluate the
18
performance of the ML-based segmentation of Left Ventricle (LV) cavity, LV myocardium, and Right Ventricle (RV) cavity. The mean volume prediction error (Mean Absolute Error in predicted volumetric measures, or MAE), 3D Hausdorff Distance (HD), and Dice coefficient were used to evaluate the performance of the segmentation. Overall, comparable performance was achieved on all variability factors including scanner vendors, scanner tube current, pixel resolution, slice thickness, age group, and gender.
Compared to a reference standard established from three expert readers, the ML-based model is capable of segmenting the LV cavity with less than 10% difference in MAE. a Dice coefficient above 86%, a HD below 9.5 mm. and an EF bias of 1.3% with a 95% confidence interval of I-12. 14]. Similarly, the RV cavity is segmented with less than 18% MAE, a Dice coefficient above 85%, a HD below 18 mm, and an EF bias of -5.5% with a 95% confidence interval of [-15, 4.4]. Lastly, the LV myocardium is segmented with less than 17% MAE, a Dice coefficient above 82%, and a HD below 15 mm.
VIII. CONCLUSION
The information submitted in this premarket notification, including the performance testing and predicate device comparison, support the safety and effectiveness of cvi42 as compared to the predicate devices when used for the defined intended use.